Image processing apparatus and image processing method

ABSTRACT

An image processing apparatus includes an edge keeping index (EKI) generating unit and a noise reducing unit. The image decoding unit decodes a data stream to generate a plurality of image comprising at least a current image having the target pixel. The adjusting unit, coupled to the image decoding unit, comprises an edge keeping index (EKI) generating unit, for generating an edge intensity value of the target pixel according to an original luminance value of the target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel, and a noise reducing unit, coupled to the EKI generating unit, for determining a first adjusted luminance value of the target pixel according to the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel, and for generating a static adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value and a first adjustment value of the target pixel. The adjustment value is determined by the edge intensity value.

CROSS REFERENCE TO RELATED PATENT APPLICATIONS

This patent application claims priority from Taiwan Patent Application No. 098114010, filed in the Taiwan Patent Office on Apr. 28, 2009, and incorporates the Taiwan patent application in its entirety by reference.

TECHNICAL FIELD

The present disclosure relates to an image processing apparatus, and more particularly, to an image processing apparatus and image processing method capable of determining a noise processing level according to an edge keeping index (EKI) of the image.

BACKGROUND OF THE PRESENT DISCLOSURE

In a common television (TV) system, noise processing is performed on an image data (e.g., a frame or a field) to adjust a luminance value of the image data, and the adjusted image data is further processed and displayed on a TV display. However, during the noise processing, a same noise processing approach is applied on each pixel of the image data; that is, regardless of complexity on details of various blocks, e.g., blocks with complicated details (such as lawns or leaves) or blocks with simple details (such as the sky or the skin of a person) in the image, the same noise processing level is used. Accordingly, when high-level noise processing is used, the area having complicated details is excessively processed such that image details become too obscure to be displayed. When low-level noise processing is used, the noise processing may be unsatisfactory for blocks with simple details, such that noise is not effectively restrained to undesirably affect image quality.

SUMMARY OF THE PRESENT DISCLOSURE

Therefore, one object of the present disclosure is to provide an image processing apparatus and an image processing method capable of determining a noise processing level according to an EKI of the image to solve the foregoing problem.

According to an embodiment of the present disclosure, an image processing apparatus comprises an image decoding unit and an image adjusting unit. The image decoding unit decodes a data stream to generate a plurality of image comprising at least a current image having the target pixel. The adjusting unit, coupled to the image decoding unit, comprises an edge keeping index (EKI) generating unit, for generating an edge intensity value of the target pixel according to an original luminance value of the target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel, and a noise reducing unit, coupled to the EKI generating unit, for determining a first adjusted luminance value of the target pixel according to the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel, and for generating a static adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value and a first adjustment value of the target pixel. The adjustment value is determined by the edge intensity value.

According to another embodiment of the present disclosure, an image processing method comprises decoding a data stream to generate a plurality of image comprising at least one current image having the target pixel; determining an edge intensity value of the target pixel according to an original luminance value of a target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel; generating a first adjusted luminance value of the target pixel according to the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel at the current image; and determining a static adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value and a first adjustment value; wherein the first adjustment value is determined by the edge intensity value.

According to another embodiment of the present disclosure, an image processing apparatus comprises an image decoding unit and an image adjusting unit. The image decoding unit, for decoding a data stream to generate a plurality of image comprising a current image having the target pixel and a previous image having a corresponding pixel mapping to the target pixel. The image adjusting unit, coupled to the image decoding unit, comprises an EKI generating unit, for generating an original EKI, a first EKI and a dynamic noise-reduced EKI of the corresponding pixel according to an original luminance value, a first adjustment value and a dynamic adjusted luminance value of the corresponding pixel, and a noise reducing unit, coupled to the EKI generating unit, for determining a first adjusted luminance value of the target pixel according to an original luminance value of a target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel, and for generating a dynamic adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value and an adjustment value of the target pixel. The adjustment value of the target pixel is obtained by adjusting an adjustment value of the corresponding pixel according to a parameter determined according to the original EKI, the first EKI and the dynamic noise-reduced EKI of the corresponding pixel.

According to an image processing apparatus and an image processing method in accordance with embodiments of the present disclosure, a noise processing level for processing a pixel data of an image data is determined according to an EKI. Accordingly, noise processing with a proper level is performed on the pixel data of the image to improve image quality.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an image processing apparatus in accordance with a first embodiment of the present disclosure.

FIG. 2 is a flowchart of processing a data stream by the image processing apparatus illustrated in FIG. 1.

FIG. 3 is a schematic diagram of a field.

FIG. 4 is a characteristics curve diagram of an original EKI and an adjustment value.

FIG. 5 is a schematic diagram of a plurality of fields.

FIG. 6 is a schematic diagram of a plurality of blocks of a dynamic noise-reduced EKI_(DNR).

FIG. 7 is a schematic diagram of an image processing apparatus in accordance with a second embodiment of the present disclosure.

FIG. 8 is a schematic diagram of an image processing apparatus in accordance with a third embodiment of the present disclosure.

FIG. 9 is a flowchart of processing a data stream by an image processing apparatus illustrated in FIG. 8.

FIG. 10 is a schematic diagram of an image processing apparatus in accordance with a fourth embodiment of the present disclosure.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Refer to FIG. 1 showing an image processing apparatus 100 in accordance with a first embodiment of the present disclosure. The image processing apparatus comprises an image decoding unit 110, an image adjusting unit 120, a de-interlacing unit 130 and an image scaling unit 140. The image adjusting unit 120 comprises a noise reducing unit 122 and an edge keeping index (EKI) generating unit 124. In addition, the image processing apparatus 100 is implemented via a hardware or software approach.

Referring to FIG. 1 and FIG. 2, FIG. 2 is a flowchart of processing a data stream D_(stream) by the image processing apparatus 100. Note that, the steps in the flowchart need not be performed as the sequence shown in FIG. 2 nor be successive, provided that the same result is substantially achieved. In Step 200, the image decoding unit 110 decodes the data stream D_(stream) to generate a plurality of fields D_(field).

FIG. 3 is a schematic diagram of a field 300 comprising luminance values of pixels P11, P12, P13 . . . . In Step 202, taking the field 300 for example, the EKI generating unit 124 calculates an edge intensity value of each pixel of the field 300. Taking a pixel P₁₃ for example, an edge intensity value Y₁₃ _(—) _(e) of the pixel P₁₃ is obtained by: Y ₁₃ _(—) _(e) =|Y ₁₁ −Y ₁₂ |+|Y ₁₂ −Y ₁₃ |+|Y ₁₃ −Y ₁₄ |+|Y ₁₄ −Y ₁₅|; Y ₁₃ _(—) _(e) =|Y ₁₁ −Y ₁₃|+2*|Y ₁₂ −Y ₁₄ |+|Y ₁₃ −Y ₁₅|; Y ₁₃ _(—) _(e)=|max(Y ₁₁ ˜Y ₁₅)−min(Y ₁₁ ˜Y ₁₅)|;

where Y₁₁ to Y₁₅ are respectively original luminance values of pixels P₁₁ to P₁₅, max(Y₁₁˜Y₁₅) is a maximum luminance value among Y₁₁ to Y₁₅, and min (Y₁₁˜Y₁₅) is a minimum luminance value among Y₁₁ to Y₁₅. It is to be noted that, other algorithms may also be used for calculating the edge intensity value, and a designer may use different calculation formulas adaptive to his design considerations to generate the edge intensity value of a pixel P_(xy), provided that the edge intensity value of the pixel P_(xy) is determined according to original luminance values of the pixel P_(xy) and at least one neighboring pixel associated with the pixel P_(xy).

In Step 204, taking the pixel P₁₃ for example, the noise reducing unit 122 determines two adjustment values W₁ and 1−W₁ according to an edge intensity value Y₁₃ _(—) _(e) generated by the EKI generating unit 124. The adjustment value W₁ is determined according to a characteristics curve 400 illustrated in FIG. 4, and the adjustment value W₁ is directly proportional to the edge intensity value Y₁₃ _(—) _(e). It is to be noted that, in other embodiments of the present disclosure, the adjustment value W₁ may be determined via a lookup table, and these design modifications are within the scope and spirit of the present disclosure.

In Step 206, the noise reducing unit 122 performs a noise reducing calculation on each of the pixels of the field 300 to generate a plurality of first adjusted luminance values corresponding to the pixels. Taking the pixel P₁₃ of the field 300 for example, a first adjusted luminance value Y′₁₃ of the pixel P₁₃ is calculated as: Y′ ₁₃ =a ₁ *Y ₁₁ +a ₂ *Y ₁₂ +a ₃ *Y ₁₃ +a ₄ *Y ₁₄ +a ₅ *Y ₁₅,

where Y₁₁, Y₁₂, Y₁₃, Y₁₄ and Y₁₅ are original luminance values of the pixels P₁₁, P₁₂, P₁₃, P₁₄ and P₁₅, and a₁, a₂, a₃, a₄ and a₅ are constants such as 1/9, 2/9, 3/9, 2/9 and 1/9, respectively. When a first adjusted luminance value Y_(xy)′ of a pixel P_(xy) is to be calculated, the noise reducing unit 122 by weighted averaging the pixel P_(xy) to horizontally adjacent pixels to generate the first adjusted luminance value Y_(xy)′ of the pixel P_(xy). Accordingly, the noise reducing unit 122 calculates the plurality of first adjusted luminance values Y₁₁′, Y₁₂′, Y₁₃′ . . . of the pixels P₁₁, P₁₂, P₁₃ . . . respectively.

Note that the foregoing formulas for calculating the first adjusted luminance values Y₁₁′, Y₁₂′, Y₁₃′ . . . are described as an example, and other approaches may be applied to other embodiments of the present disclosure to calculate a first adjusted luminance value of each of the pixels. For example, two-dimensional (2D) adjacent pixels are used for adjusting a luminance value of a pixel P₂₂ of the field 300, and a first adjusted luminance value Y₂₂′ of the pixel P₂₂ is calculated as: Y ₂₂ ′=a ₁₁ *Y ₁₁ +a ₁₂ *Y ₁₂ +a ₁₃ *Y ₁₃ +a ₂₁ *Y ₂₁ +a ₂₂ *Y ₂₂ +a ₂₃ *Y ₂₃ +a ₃₁ *Y ₃₁ +a ₃₂ *Y ₃₂ +a ₃₃ *Y ₃₃,

where Y₁₁ to Y₃₃ are original luminance values of pixels P₁₁ to P₃₃, and a₁₁ to a₃₃ are constants. In other words, provided that the first adjusted luminance value Y_(xy)′ of the pixel P_(xy) is determined according to the pixel P_(xy) and an original luminance value of at least one neighboring pixel associated with the pixel P_(xy), the approach for calculating the first adjusted luminance values Y₁₁′, Y₁₂′, Y₁₃′ . . . can be modified to adapt to considerations of users.

After the plurality of first adjusted luminance values Y₁₁′, Y₁₂′, Y₁₃′ . . . of the pixels P₁₁, P₁₂, P₁₃ . . . are calculated, in Step 208, the noise reducing unit 122 calculates each of the pixels of the field 300 to generate a static adjusted luminance value corresponding to each of the pixels. Taking the pixel P₁₂ of the field 300 for example, a static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ is calculated as: Y ₁₂ _(—) _(SNR) =W ₁ *Y ₁₂+(1−W ₁)*Y′ ₁₂,

where Y₁₂ and Y₁₂′ are respectively an original luminance value and a first adjusted luminance value of the pixel P₁₂, and W₁ is an adjustment value determined via a characteristics curve 400 illustrated in FIG. 4. In other words, the Y₁₂ _(—) _(SNR) of the pixel P₁₂ is obtained through by weight adding the original luminance value Y₁₂ of the pixel P₁₂ to the first adjusted luminance value Y′₁₂. A weight value of the original luminance value Y₁₂ is W₁, and a weight value of the first adjusted luminance value Y′₁₂ is 1−W₁.

For other pixels of the field 300, the noise reducing unit 122 generates an adjusted image data by similarly implementing the foregoing approach of calculating the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂.

The concept of calculating a static adjusted luminance value of a pixel is briefly described below. Generally, image edges are blurred after noise reducing process is performed, and thus to prevent the undesirable blurred image edges, the noise reducing unit 122 according to an embodiment of the present disclosure determines a proper noise processing level via the edge intensity value Y₁₂ _(—) _(e). For example, when the pixel P₁₂ is near an edge, the edge intensity value Y₁₂ _(—) _(e) is quite large such that the adjustment value W₁ is also large. Supposing the adjustment value W₁ is 0.95, the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ is calculated as: Y ₁₂ _(—) _(SNR)=0.95*Y ₁₂+0.05*Y′ ₁₂,

That is, less noise processing is performed on the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ (the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ approximates the original luminance value Y₁₂). On the contrary, when the pixel P₁₂ is not near the edge, the edge intensity value Y₁₂ _(—) _(e) is quite small such that the adjustment value W₁ is also small. Supposing that the adjustment value W₁ is 0.1, the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ is calculated as: Y ₁₂ _(—) _(SNR)=0.1*Y ₁₂+0.9*Y′ ₁₂

That is, more noise processing is performed on the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ (the static adjusted luminance value Y₁₂ _(—) _(SNR) of the pixel P₁₂ approximates the first adjusted luminance value Y′₁₂). Therefore, the image processing apparatus 100 performs more noise processing on a pixel that is not near an edge, and performs less noise processing on a pixel that is near an edge, so as to avoid the blur of the image edges. Therefore, according to the present disclosure, an optimal noise processing effect is achieved without excessively blurring the image edges.

After the noise reducing unit 122 generates a plurality of adjusted fields D_(SNR) corresponding pixels of a plurality of fields D_(field) (not shown), with a luminance value of each of the plurality of adjusted fields D_(SNR) being the foregoing static adjusted luminance value, the noise reducing unit 122 performs a dynamic noise reducing process on the plurality of adjusted fields D_(SNR) to further improve image quality. An operation flow of performing a dynamic noise reducing by the noise reducing unit 122 is described below.

In Step 210, the EKI generating unit 124 sums up edge intensity values Y₁₁ _(—) _(e), Y₁₂ _(—) _(e), Y₁₂ _(—) _(e) . . . of the plurality of pixels (or pixels of a whole image), to generate an original EKI_(o): EKI_(o)=Sum(Y ₁₁ _(—) _(e) ,Y ₁₂ _(—) _(e) ,Y ₁₃ _(—) _(e) . . . ).

The EKI generating unit 124 generates a first EKI₁ and a dynamic noise-reduced EKI_(DNR) by implementing the calculation approach similar to that of the original EKI_(o). However, original luminance values of the pixels are used for calculating the original EKI_(o), first adjusted luminance values of pixels are used for calculating the first EKI₁, and dynamic adjusted luminance values of pixels are used for calculating the dynamic noise-reduced EKI_(DNR). Taking the first EKI₁ for example, a first edge intensity value Y′₁₃ _(—) ₁ _(—) _(e) is calculated as: Y′ ₁₃ _(—) ₁ _(—) _(e) =|Y′ ₁₁ _(—) ₁ −Y′ ₁₂ _(—) ₁ |+|Y′ ₁₂ _(—) ₁ −Y′ ₁₃ _(—) ₁ |+|Y′ ₁₃ _(—) ₁ −Y′ ₁₄ _(—) ₁ |+|Y′ ₁₄ _(—) ₁ −Y′ ₁₅ _(—) ₁|,

where Y′₁₁ _(—) ₁ to Y′₁₅ _(—) ₁ are first luminance values of the pixels P₁₁ to P₁₅ at a field F₀ _(—) _(even). After calculating the first edge intensity values Y′₁₁ _(—) ₁ _(—) _(e), Y′₁₂ _(—) ₁ _(—) _(e), Y′₁₃ _(—) ₁ _(—) _(e) . . . of the pixels P₁₁, P₁₂, P₁₃ . . . , the EKI generating unit 124 sums up the first edge intensity values Y′₁₁ _(—) ₁ _(—) _(e), Y′₁₂ _(—) ₁ _(—) _(e), Y′₁₃ _(—) ₁ _(—) _(e) . . . of the plurality of pixels (or pixels of a whole image) to generate the first EKI₁ represented as: EKI₁=SUM(Y′ ₁₁ _(—) ₁ _(—) _(e) ,Y′ ₁₂ _(—) ₁ _(—) _(e) ,Y′ ₁₃ _(—) ₁ _(—) _(e) . . . ).

In addition, the calculation approach for calculating the dynamic noise-reduced EKI_(DNR) can be deduced from the foregoing description, and details shall not be described for brevity.

It is to be noted that, the step of calculating the original EKI_(o), the first EKI₁ and the dynamic noise-reduced EKI_(DNR) may be interleaved between Step 208 and Step 210 or be performed at other proper time points. In addition, the original EKI_(o), the first EKI₁ and the dynamic noise-reduced EKI_(DNR) may be calculated at different time points.

FIG. 5 is a schematic diagram of a plurality of fields D_(field) comprising F₀ _(—) _(even), F₀ _(—) _(odd), F₁ _(—) _(even) and F₁ _(—) _(odd. F) ₀ _(—) _(even) is an even field of a previous field, F₀ _(—) _(odd) is an odd field of the previous field, F₁ _(—) _(even) is an even field of a current field, and F₁ _(—) _(odd) is an odd field of the current field. In addition, F₀ _(—) _(even) and F₁ _(—) _(even) have pixels at same positions of an image; that is, pixels P₁₁, P₁₂ and P₁₃, of F₀ _(—) _(even) and F₁ _(—) _(even), illustrated in FIG. 5 are at the same positions of the image.

Referring to FIG. 1, FIG. 2 and FIG. 5, in Step 206 illustrated in FIG. 2, suppose that the noise reducing unit 122 performs dynamic noise reducing with respect to the adjusted field F₁ _(—) _(even). Take the pixel P₁₂ illustrated in FIG. 5 for example. Supposing that the noise reducing unit 122 determines an adjustment value W₂ of the current field F₁ _(—) _(even) according to the original EKI_(o), the first EKI₁ and the dynamic noise-reduced EKI_(DNR) of the even field F₀ _(—) _(even) (or the odd field F₀ _(—) _(odd)) prior to the current field F₁ _(—) _(even). In Step 212, the noise reducing unit 122 determines the adjustment value W₂ of the field F₁ _(—) _(even) according to which block illustrated in FIG. 6 the dynamic noise-reduced EKI_(DNR) of the even field F₀ _(—) _(even) prior to the current field F₁ _(—) _(even) lies in. More particularly, an upper boundary a illustrated in FIG. 6 is the original EKI_(o) of the field F₀ _(—) _(even), and a lower boundary b is the first EKI₁. When the dynamic noise-reduced EKI_(DNR) lies in block 2, the adjustment value W₂ is equal to 1; when the dynamic noise-reduced EKI_(DNR) lies in block 3, the adjustment value W₂ is greater than 1. Note that the number of blocks is described for illustration purposes only; that is, the number and ranges of the blocks and the adjustment value W₂ corresponding to the blocks may be modified to adapt to various design considerations. In addition, the adjustment value W₂ may be determined via a lookup table according to the dynamic noise-reduced EKI_(DNR), and the design modifications are within the scope and spirit of the present disclosure.

In Step 214, taking the pixel P₁₂ of the field F₁ _(—) _(even) for example, the noise reducing unit 122 determines a dynamic adjusted luminance value Y₁ _(—) ₁₂ _(—) _(DNR) of the pixel P₁₂ according to the original luminance value Y₁ _(—) ₁₂ of the pixel P₁₂, the first adjusted luminance value Y′₁ _(—) ₁₂, the adjustment value W₁ and the adjustment value W₂. The dynamic adjusted luminance value Y₁ _(—) ₁₂ _(—) _(DNR) of the pixel P₁₂ at the current field F₁ _(—) _(even) is calculated as: Y ₁ _(—) ₁₂ _(—) _(DNR) =W ₃ *Y ₁ _(—) ₁₂+(1−W ₃)*Y′ ₁ _(—) ₁₂,

where the adjustment value W₃ is equal to W_(i)*W₂.

After that, the image adjusting unit 120 performs the foregoing calculation on all pixels of the field D_(field) to generate a plurality of noise-reduced fields D_(field)′ to the de-interlacing unit 130.

In Step 216, the de-interlacing unit 130 de-interlaces the plurality of dynamic noise-reduced fields D_(field)′ to generate a plurality of frames D_(frame). In Step 218, the image scaling unit 140 scales the plurality of frame D_(frame) to generate a plurality of display data D_(out) to a display.

It is to be noted that, in another embodiment illustrated in FIG. 1, the image adjusting unit 120 need not perform the dynamic noise processing; that is, the adjusted field D_(SNR) outputted by the dynamic noise reducing unit 122 may also be directly outputted by the image adjusting unit 120, and is then de-interlaced by the de-interlacing unit 130 to generate the plurality of frames D_(frame)—such design modifications are within the scope and spirit of the present disclosure.

FIG. 7 is a schematic diagram of an image processing apparatus 700 in accordance with a second embodiment of the present disclosure. The image processing apparatus 700 comprises an image decoding unit 710, a de-interlacing unit 720, an image adjusting unit 730 and an image scaling unit 740. The image adjusting unit 730 comprises a noise reducing unit 732 and an EKI generating unit 734. In addition, the image processing apparatus 700 is implemented via a hardware or software approach.

A difference between the image processing apparatus 700 and the image processing apparatus 100 illustrated in FIG. 1 is that the image adjusting unit 120 of the image processing apparatus 100 adjusts field and the image adjusting unit 730 of the image processing apparatus 700 adjusts frame. In addition, operations of the image adjusting unit 730 are similar to those of the image adjusting unit 120. Therefore, the operation flow of the image processing apparatus 700 is easily deduced by a person having ordinary skill in the art after reading the description associated with the image processing apparatus 100, and details thereof shall not be described for brevity.

FIG. 8 is a schematic diagram of an image processing apparatus 800 in accordance with a third embodiment of the present disclosure. The image processing apparatus 800 comprises an image decoding unit 810, an image adjusting unit 820, a de-interlacing unit 830 and an image scaling unit 840. The image adjusting unit 820 comprises a noise reducing unit 822 and an EKI generating unit 824. In addition, the image processing apparatus is implemented via a hardware or software approach.

Referring to FIG. 8 and FIG. 9, FIG. 9 is a flowchart of performing image processing on a data stream D_(stream) by the image processing apparatus 800. Note that, the steps in the flowchart need not be performed as the sequence shown in FIG. 9 nor be successive, provided that the same result is substantially achieved. In Step 900, an image decoding unit 810 decodes the data stream D_(steam) to generate the plurality of fields D_(field) illustrated in FIG. 5.

In Step 902, referring to FIG. 5, FIG. 8 and FIG. 9, suppose that the image adjusting unit 820 adjusts the field F₁ _(—) _(even). Taking the pixel P₁₂ illustrated in FIG. 5 for example, suppose that the dynamic adjusted luminance value Y₀ _(—) ₁₂ _(—) _(DNR) of the pixel P₁₂ at the previous field F₀ _(—) _(even) prior to the current filed data F₁ _(—) _(even) is calculated as: Y ₀ _(—) ₁₀ _(—) _(DNR) =W ₀ _(—) ₃ *Y ₀ _(—) ₁₂+(1−W ₀ _(—) ₃)*Y′ ₀ _(—) ₁₂,

where Y₀ _(—) ₁₂ is an original luminance value of the pixel P₁₂ at the previous field F₀ _(—) _(even), Y′₀ _(—) ₁₂ is a first adjusted luminance value of the pixel P₁₂ at the previous field F₀ _(—) _(even), and W₀ _(—) ₃ is an adjustment value. The noise reducing unit 822 first determines a parameter W₂ of the current filed data F₁ _(—) _(even) according to an original EKI_(O), a first EKI₁ and a dynamic noise-reduced EKI_(DNR). Note that, the calculation approach of calculating the original EKI_(o), the first EKI₁ and the dynamic noise-reduced EKI_(DNR) is described in detail in the embodiment with reference to FIG. 1, and the method for determining the parameter W₂ is similar to Step 212 illustrated in FIG. 2 (referring to FIG. 6, the parameter W₂ is the adjustment value W₂ in accordance with the embodiment illustrated in FIG. 1), so that details shall not be described for brevity.

In Step 904, taking the pixel P₁₂ at the current field F₁ _(—) _(even) for example, the noise reducing unit 822 determines the dynamic adjusted luminance value Y₁ _(—) ₁₂ _(—) _(DNR) of the pixel P₁₂ according to an original luminance value Y₁ _(—) ₁₂ of the pixel P₁₂ at the current field F₁ _(—) _(even), the first adjusted luminance value Y′₁ _(—) ₁₂, the adjustment value W₀ _(—) ₃ of a previous field and the parameter W₂. The dynamic adjusted luminance value Y₁ _(—) ₁₂ _(—) _(DNR) of the pixel P₁₂ at the current field F₁ _(—) _(even) is calculated as: Y ₁ _(—) ₁₂ _(—) _(DNR) =W ₁ _(—) ₃ *Y ₁ _(—) ₁₂+(1−W ₁ _(—) ₃)*Y′ ₁ _(—) ₁₂,

where the adjustment value W₁ _(—) ₃ is equal to W₀ _(—) ₃*W₂. More particularly, the adjustment value W₁ _(—) ₃ of a current field is generated via a recursive calculation, which applies the parameter W₂ to adjust an adjustment value W₀ _(—) ₃ of the previous field. The parameter W₂ is determined according to a distribution of the original EKI₀ of the previous even field F₀ _(—) _(even), the first EKI₁ and the dynamic noise-reduced EKI_(DNR). The adjustment value W₀ _(—) ₃ is generated by adjusting a previous adjustment value, and the approach is the same as that for obtaining the adjustment value W₁ _(—) ₃, so that details shall not be described for brevity.

The image adjusting unit 820 performs the foregoing calculation on all pixels to generate a plurality of adjusted fields D_(field)′ to be transmitted to the de-interlacing unit 830.

In Step 906, the de-interlacing unit 830 de-interlaces the plurality of dynamic noise-reduced fields D_(field)′ to generate a plurality of frames D_(frame). In Step 908, the image scaling unit 840 scales the plurality of frames D_(frame) to generate a plurality of display data D_(out) to be transmitted to a display.

FIG. 10 is a schematic diagram of an image processing apparatus 1000 in accordance with a fourth embodiment of the present disclosure. The image processing apparatus 1000 comprises an image decoding unit 1010, a de-interlacing unit 1020, an image adjusting unit 1030 and an image scaling unit 1040. The image adjusting unit 1030 comprises a noise reducing unit 1032 and an EKI generating unit 1034. In addition, the image processing apparatus 1000 is implemented via a hardware or software approach.

A difference between the image processing apparatus 1000 and the image processing apparatus 800 illustrated in FIG. 8 is that the image adjusting unit 820 of the image processing apparatus 800 adjusts field and the image adjusting unit 1030 of the image processing apparatus 1000 adjusts frame. Other than that, operations of the image adjusting unit 1030 are similar to those of the image adjusting unit 820. Therefore, the operation flow of the image processing apparatus 1000 is easily deduced by a person having ordinary skill in the art after reading the description associated with the image processing apparatus 800, and details thereof shall not be described for brevity.

In conclusion, according to an image processing apparatus and an image processing method in accordance with an embodiment of the present disclosure, a noise processing level of a pixel data of an image is determined according to an EKI of the pixel. Accordingly, noise processing with a proper level is performed on the pixel data of the image to improve image quality.

While the disclosure has been described in terms of what is presently considered to be the most practical and preferred embodiments, it is to be understood that the present disclosure needs not to be limited to the above embodiments. On the contrary, it is intended to cover various modifications and similar arrangements included within the spirit and scope of the appended claims which are to be accorded with the broadest interpretation so as to encompass all such modifications and similar structures. 

1. An image processing apparatus for adjusting luminance of a target pixel, the apparatus comprising: an image decoding unit, that decodes a data stream to generate a plurality of images comprising a current image having the target pixel; and an adjusting unit, coupled to the image decoding unit, comprising: an edge keeping index (EKI) generating unit, that generates an edge intensity value for the target pixel according to an original luminance value of the target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel; and a noise reducing unit, coupled to the EKI generating unit, that determines a first adjusted luminance value of the target pixel according to the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel, and that generates a static adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value, and a first adjustment value of the target pixel, the adjustment value being determined according to the edge intensity value.
 2. The image processing apparatus as claimed in claim 1, wherein the EKI generating unit generates the edge intensity value of the target pixel by calculating a difference between the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel.
 3. The image processing apparatus as claimed in claim 1, wherein the noise reducing unit generates the first adjusted luminance value of the target pixel by weighted averaging the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel according to the adjustment value of the target pixel.
 4. The image processing apparatus as claimed in claim 1, wherein the first adjustment value is directly proportional to the edge intensity value.
 5. The image processing apparatus as claimed in claim 1, wherein the plurality of image further comprise a previous image having a corresponding pixel mapped to the target pixel of the current image, and wherein the noise reducing unit further determines a second adjustment value of the target pixel according to an original EKI, a first EKI and a dynamic noise-reduced EKI of the corresponding pixel, and further determines a dynamic adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value, and the second adjustment value of the target pixel.
 6. The image processing apparatus as claimed in claim 5, wherein the noise reducing unit generates the dynamic adjusted luminance value of the target pixel by weighted averaging the original luminance value and the first adjusted luminance value of the target pixel according to the first adjustment value and the second adjustment value.
 7. The image processing apparatus as claimed in claim 5, wherein the noise reducing unit determines a third adjustment value according to the first adjustment value and the second adjustment value, and further generates the dynamic adjusted luminance value by weighted averaging the original luminance value and the first adjusted luminance value of the target pixel according to the third adjustment value.
 8. An apparatus capable of adjusting luminance of a target pixel, the apparatus comprising: a processor configured to perform operations comprising: decoding a data stream to generate a plurality of images comprising a current image having the target pixel; determining an edge intensity value of the target pixel according to an original luminance value of the target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel; generating a first adjusted luminance value of the target pixel according to the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel; and determining a static adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value, and a first adjustment value, the first adjustment value being determined according to the edge intensity value.
 9. The apparatus as claimed in claim 8, wherein the format of the plurality of image is one of field and frame.
 10. The apparatus as claimed in claim 8, wherein the edge intensity value is obtained by calculating a difference between the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel.
 11. The apparatus as claimed in claim 8, wherein the first adjustment value is generated by weighted averaging the original luminance value of the target pixel and the original luminance value of the at least one neighboring pixel associated with the target pixel.
 12. The apparatus as claimed in claim 8, wherein the first adjustment value is directly proportional to the edge intensity value.
 13. The apparatus as claimed in claim 8, the plurality of image data further comprising a previous image having a corresponding pixel mapped to the target pixel of the current image, the processor further configured to perform operations comprising: determining a second adjustment value of the target pixel according to an original EKI, a first EKI and a dynamic noise-reduced EKI of the corresponding pixel; and determining a dynamic adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value, and the second adjustment value of the target pixel.
 14. The apparatus as claimed in claim 13, wherein the dynamic adjusted luminance value is generated by weighted averaging the original luminance value and the first adjusted luminance value of the target pixel.
 15. An image processing apparatus for adjusting the luminance of a target pixel, the apparatus comprising: an image decoding unit, that decodes a data stream to generate a plurality of images comprising a current image having the target pixel and a previous image having a corresponding pixel mapped to the target pixel; and an image adjusting unit, coupled to the image decoding unit, comprising: an EKI generating unit, that generates an original EKI, a first EKI, and a dynamic noise-reduced EKI of the corresponding pixel according to an original luminance value, a first adjustment value, and a dynamic adjusted luminance value of the corresponding pixel; and a noise reducing unit, coupled to the EKI generating unit, that determines a first adjusted luminance value of the target pixel according to an original luminance value of the target pixel and an original luminance value of at least one neighboring pixel associated with the target pixel, and that generates a dynamic adjusted luminance value of the target pixel according to the original luminance value, the first adjusted luminance value, and an adjustment value of the target pixel, the adjustment value of the target pixel being obtained by adjusting an adjustment value of the corresponding pixel according to a parameter determined according to the original EKI, the first EKI, and the dynamic noise-reduced EKI of the corresponding pixel.
 16. The image processing apparatus as claimed in claim 15, wherein the noise reducing unit generates the dynamic adjusted luminance value of the target pixel by weighted averaging the original luminance value and the first adjusted luminance value of the target pixel.
 17. The image processing apparatus as claimed in claim 16, wherein the noise reducing unit determines the adjustment value of the target pixel according to the parameter and the adjustment value of the corresponding pixel, and generates the dynamic adjusted luminance value by weighted averaging the original luminance value and the first adjusted luminance value of the target pixel according to the adjustment value. 